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Artificial Neuron using Vertical MoS(2)/Graphene Threshold Switching Memristors
With the ever-increasing demand for low power electronics, neuromorphic computing has garnered huge interest in recent times. Implementing neuromorphic computing in hardware will be a severe boost for applications involving complex processes such as image processing and pattern recognition. Artifici...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6328611/ https://www.ncbi.nlm.nih.gov/pubmed/30631087 http://dx.doi.org/10.1038/s41598-018-35828-z |
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author | Kalita, Hirokjyoti Krishnaprasad, Adithi Choudhary, Nitin Das, Sonali Dev, Durjoy Ding, Yi Tetard, Laurene Chung, Hee-Suk Jung, Yeonwoong Roy, Tania |
author_facet | Kalita, Hirokjyoti Krishnaprasad, Adithi Choudhary, Nitin Das, Sonali Dev, Durjoy Ding, Yi Tetard, Laurene Chung, Hee-Suk Jung, Yeonwoong Roy, Tania |
author_sort | Kalita, Hirokjyoti |
collection | PubMed |
description | With the ever-increasing demand for low power electronics, neuromorphic computing has garnered huge interest in recent times. Implementing neuromorphic computing in hardware will be a severe boost for applications involving complex processes such as image processing and pattern recognition. Artificial neurons form a critical part in neuromorphic circuits, and have been realized with complex complementary metal–oxide–semiconductor (CMOS) circuitry in the past. Recently, metal-insulator-transition materials have been used to realize artificial neurons. Although memristors have been implemented to realize synaptic behavior, not much work has been reported regarding the neuronal response achieved with these devices. In this work, we use the volatile threshold switching behavior of a vertical-MoS(2)/graphene van der Waals heterojunction system to produce the integrate-and-fire response of a neuron. We use large area chemical vapor deposited (CVD) graphene and MoS(2), enabling large scale realization of these devices. These devices can emulate the most vital properties of a neuron, including the all or nothing spiking, the threshold driven spiking of the action potential, the post-firing refractory period of a neuron and strength modulated frequency response. These results show that the developed artificial neuron can play a crucial role in neuromorphic computing. |
format | Online Article Text |
id | pubmed-6328611 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-63286112019-01-14 Artificial Neuron using Vertical MoS(2)/Graphene Threshold Switching Memristors Kalita, Hirokjyoti Krishnaprasad, Adithi Choudhary, Nitin Das, Sonali Dev, Durjoy Ding, Yi Tetard, Laurene Chung, Hee-Suk Jung, Yeonwoong Roy, Tania Sci Rep Article With the ever-increasing demand for low power electronics, neuromorphic computing has garnered huge interest in recent times. Implementing neuromorphic computing in hardware will be a severe boost for applications involving complex processes such as image processing and pattern recognition. Artificial neurons form a critical part in neuromorphic circuits, and have been realized with complex complementary metal–oxide–semiconductor (CMOS) circuitry in the past. Recently, metal-insulator-transition materials have been used to realize artificial neurons. Although memristors have been implemented to realize synaptic behavior, not much work has been reported regarding the neuronal response achieved with these devices. In this work, we use the volatile threshold switching behavior of a vertical-MoS(2)/graphene van der Waals heterojunction system to produce the integrate-and-fire response of a neuron. We use large area chemical vapor deposited (CVD) graphene and MoS(2), enabling large scale realization of these devices. These devices can emulate the most vital properties of a neuron, including the all or nothing spiking, the threshold driven spiking of the action potential, the post-firing refractory period of a neuron and strength modulated frequency response. These results show that the developed artificial neuron can play a crucial role in neuromorphic computing. Nature Publishing Group UK 2019-01-10 /pmc/articles/PMC6328611/ /pubmed/30631087 http://dx.doi.org/10.1038/s41598-018-35828-z Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Kalita, Hirokjyoti Krishnaprasad, Adithi Choudhary, Nitin Das, Sonali Dev, Durjoy Ding, Yi Tetard, Laurene Chung, Hee-Suk Jung, Yeonwoong Roy, Tania Artificial Neuron using Vertical MoS(2)/Graphene Threshold Switching Memristors |
title | Artificial Neuron using Vertical MoS(2)/Graphene Threshold Switching Memristors |
title_full | Artificial Neuron using Vertical MoS(2)/Graphene Threshold Switching Memristors |
title_fullStr | Artificial Neuron using Vertical MoS(2)/Graphene Threshold Switching Memristors |
title_full_unstemmed | Artificial Neuron using Vertical MoS(2)/Graphene Threshold Switching Memristors |
title_short | Artificial Neuron using Vertical MoS(2)/Graphene Threshold Switching Memristors |
title_sort | artificial neuron using vertical mos(2)/graphene threshold switching memristors |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6328611/ https://www.ncbi.nlm.nih.gov/pubmed/30631087 http://dx.doi.org/10.1038/s41598-018-35828-z |
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